{"id":"https://openalex.org/W2014977754","doi":"https://doi.org/10.1109/isbi.2013.6556571","title":"Efficient GRAPPA reconstruction using random projection","display_name":"Efficient GRAPPA reconstruction using random projection","publication_year":2013,"publication_date":"2013-04-01","ids":{"openalex":"https://openalex.org/W2014977754","doi":"https://doi.org/10.1109/isbi.2013.6556571","mag":"2014977754"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2013.6556571","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2013.6556571","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE 10th International Symposium on Biomedical Imaging","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046260287","display_name":"Jingyuan Lyu","orcid":"https://orcid.org/0000-0002-1873-8869"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jingyuan Lyu","raw_affiliation_strings":["Department of Biomedical Engineering Department of Electrical Engineering, State University of New York at Buffalo, Buffalo, NY, USA","Dept. of Biomed. Eng., State Univ. of New York at Buffalo, Buffalo, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering Department of Electrical Engineering, State University of New York at Buffalo, Buffalo, NY, USA","institution_ids":["https://openalex.org/I63190737"]},{"raw_affiliation_string":"Dept. of Biomed. Eng., State Univ. of New York at Buffalo, Buffalo, NY, USA","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001829437","display_name":"Yuchou Chang","orcid":"https://orcid.org/0000-0002-9349-4008"},"institutions":[{"id":"https://openalex.org/I1324766304","display_name":"Barrow Neurological Institute","ror":"https://ror.org/01fwrsq33","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1324766304","https://openalex.org/I1325481341","https://openalex.org/I2802827176"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuchou Chang","raw_affiliation_strings":["Barrow Neurological Institute, Phoenix, AZ, USA","Barrow Neurological Institute, Phoenix, AZ USA"],"affiliations":[{"raw_affiliation_string":"Barrow Neurological Institute, Phoenix, AZ, USA","institution_ids":["https://openalex.org/I1324766304"]},{"raw_affiliation_string":"Barrow Neurological Institute, Phoenix, AZ USA","institution_ids":["https://openalex.org/I1324766304"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075561442","display_name":"Leslie Ying","orcid":"https://orcid.org/0000-0001-9801-1362"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Leslie Ying","raw_affiliation_strings":["Department of Biomedical Engineering Department of Electrical Engineering, State University of New York at Buffalo, Buffalo, NY, USA","Dept. of Biomed. Eng., State Univ. of New York at Buffalo, Buffalo, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering Department of Electrical Engineering, State University of New York at Buffalo, Buffalo, NY, USA","institution_ids":["https://openalex.org/I63190737"]},{"raw_affiliation_string":"Dept. of Biomed. Eng., State Univ. of New York at Buffalo, Buffalo, NY, USA","institution_ids":["https://openalex.org/I63190737"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5046260287"],"corresponding_institution_ids":["https://openalex.org/I63190737"],"apc_list":null,"apc_paid":null,"fwci":0.2581,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.62277995,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"1","issue":null,"first_page":"700","last_page":"703"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7534129619598389},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.7462988495826721},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.6939031481742859},{"id":"https://openalex.org/keywords/random-projection","display_name":"Random projection","score":0.6770366430282593},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.6241335868835449},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.5951534509658813},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5330518484115601},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.5071461200714111},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.4268285036087036},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39707618951797485},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19937068223953247},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10229659080505371}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7534129619598389},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.7462988495826721},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.6939031481742859},{"id":"https://openalex.org/C2777036070","wikidata":"https://www.wikidata.org/wiki/Q18393452","display_name":"Random projection","level":2,"score":0.6770366430282593},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.6241335868835449},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.5951534509658813},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5330518484115601},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.5071461200714111},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4268285036087036},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39707618951797485},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19937068223953247},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10229659080505371},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2013.6556571","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2013.6556571","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE 10th International Symposium on Biomedical Imaging","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1516726196","https://openalex.org/W1971181447","https://openalex.org/W1974528356","https://openalex.org/W2009238259","https://openalex.org/W2027937852","https://openalex.org/W2030449718","https://openalex.org/W2037757210","https://openalex.org/W2070269575","https://openalex.org/W2094568618","https://openalex.org/W2108892976","https://openalex.org/W2111388536","https://openalex.org/W2132515907","https://openalex.org/W2135508918","https://openalex.org/W2145096794","https://openalex.org/W2155369619","https://openalex.org/W2979473749","https://openalex.org/W4249560439"],"related_works":["https://openalex.org/W1637798125","https://openalex.org/W2367926634","https://openalex.org/W2064168458","https://openalex.org/W4287750422","https://openalex.org/W2004988775","https://openalex.org/W4300663657","https://openalex.org/W2951250958","https://openalex.org/W2592293938","https://openalex.org/W4221157392","https://openalex.org/W3197970974"],"abstract_inverted_index":{"As":[0],"a":[1,15,54,82,111],"data-driven":[2],"technique,":[3],"GRAPPA":[4],"has":[5],"been":[6,59],"widely":[7],"used":[8],"for":[9,23],"parallel":[10],"MRI":[11],"reconstruction.":[12,49],"In":[13,73],"GRAPPA,":[14,121],"large":[16,36,64],"amount":[17],"of":[18,38,56,66,95,119],"calibration":[19,25,100],"data":[20,109],"is":[21,44,123],"desirable":[22],"accurate":[24],"and":[26],"thus":[27],"estimation.":[28],"However,":[29],"the":[30,35,63,78,93,96,99,108],"computational":[31],"time":[32],"increases":[33],"with":[34],"number":[37,55,65],"equations":[39],"to":[40,61,69,87,91,117],"be":[41],"solved,":[42],"which":[43],"especially":[45],"serious":[46],"in":[47,98],"3-D":[48],"To":[50],"address":[51],"this":[52,74],"issue,":[53],"approaches":[57],"have":[58],"developed":[60],"compress":[62],"physical":[67],"channels":[68],"fewer":[70],"virtual":[71],"channels.":[72],"paper,":[75],"we":[76],"tackle":[77],"complexity":[79],"problem":[80,97],"from":[81],"different":[83],"prospective.":[84],"We":[85],"propose":[86],"use":[88],"random":[89],"projections":[90],"reduce":[92],"dimension":[94],"step.":[101],"Experimental":[102],"results":[103,115],"show":[104],"that":[105],"randomly":[106],"projecting":[107],"onto":[110],"lower-dimensional":[112],"subspace":[113],"yields":[114],"comparable":[116],"those":[118],"traditional":[120],"but":[122],"computationally":[124],"significantly":[125],"less":[126],"expensive.":[127]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
